NCAA® March Madness®: Bracketology with Google Cloud
Earned 4月 28, 2020 EDT
DEPRECATED Google Cloud Solutions II: Data and Machine Learning
Earned 4月 27, 2020 EDT
DEPRECATED BigQuery Basics for Data Analysts
Earned 4月 27, 2020 EDT
BigQuery for Data Warehousing
Earned 4月 27, 2020 EDT
DEPRECATED BigQuery for Data Analysis
Earned 4月 27, 2020 EDT
[DEPRECATED] Data Engineering
Earned 4月 22, 2020 EDT
Scientific Data Processing
Earned 4月 14, 2020 EDT
ベースライン: データ、ML、AI
Earned 4月 5, 2020 EDT
機械学習API
Earned 3月 27, 2020 EDT
In this series of labs you will learn how to use BigQuery to analyze NCAA basketball data with SQL. Build a Machine Learning Model to predict the outcomes of NCAA March Madness basketball tournament games.
詳細
In this advanced-level quest, you will learn how to harness serious Google Cloud computing power to run big data and machine learning jobs. The hands-on labs will give you use cases, and you will be tasked with implementing big data and machine learning practices utilized by Google’s very own Solutions Architecture team. From running Big Query analytics on tens of thousands of basketball games, to training TensorFlow image classifiers, you will quickly see why Google Cloud is the go-to platform for running big data and machine learning jobs.
詳細
Want to scale your data analysis efforts without managing database hardware? Learn the best practices for querying and getting insights from your data warehouse with this interactive series of BigQuery labs. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.
Want to learn the core SQL and visualization skills of a Data Analyst? Interested in how to write queries that scale to petabyte-size datasets? Take the BigQuery for Analyst Quest and learn how to query, ingest, optimize, visualize, and even build machine learning models in SQL inside of BigQuery.
詳細
This advanced-level quest is unique amongst the other catalog offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Data Engineer Certification. From Big Query, to Dataprep, to Cloud Composer, this quest is composed of specific labs that will put your Google Cloud data engineering knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, you will need other preparation, too. The exam is quite challenging and external studying, experience, and/or background in cloud data engineering is recommended. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of the Engineer Data in the Google Cloud to receive an exclusive Google Cloud digital badge.
機械学習はもっとも迅速に成長しているテクノロジーの分野です。Google Cloud Platformは、その成長に一役かっています。APIのホストを使うことにより、GCPにはツールがあります。この上級レベルのクエストでは、「Implementing an AI Chatbot with Dialogflow」や「Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API」と同様に機械学習APIについてハンズオンで演習ができます。
NCAA® March Madness®: Bracketology with Google Cloud
Earned 4月 28, 2020 EDT
DEPRECATED Google Cloud Solutions II: Data and Machine Learning
Earned 4月 27, 2020 EDT
DEPRECATED BigQuery Basics for Data Analysts
Earned 4月 27, 2020 EDT
BigQuery for Data Warehousing
Earned 4月 27, 2020 EDT
DEPRECATED BigQuery for Data Analysis
Earned 4月 27, 2020 EDT
[DEPRECATED] Data Engineering
Earned 4月 22, 2020 EDT
Scientific Data Processing
Earned 4月 14, 2020 EDT
ベースライン: データ、ML、AI
Earned 4月 5, 2020 EDT
機械学習API
Earned 3月 27, 2020 EDT